Overview
Severe brain injuries can leave people in states where they are unconscious or only partly aware, such as a coma. These conditions are common after injuries like head trauma or bleeding in the brain. One of the biggest challenges for doctors is knowing if - or when - a patient will wake up and regain awareness.
This research study is being done to determine if patterns in brain activity during sleep (measured by EEG) can help doctors better predict how quickly someone will wake up and recover after a serious brain injury, as well as how well they might do in the long term. It also aims to develop new ways of using EEG to track how the brain's networks heal and reconnect over time.
Description
Disorders of consciousness (DoC), including coma and other states of impaired awareness, are common following severe acute brain injury, particularly traumatic brain injury (TBI) and intracerebral hemorrhage (ICH). Predicting whether and when these patients will recover consciousness remains one of the greatest challenges in neurocritical care. Current prognostic tools are limited, and inaccurate predictions may influence critical decisions regarding ongoing treatment and goals of care.
Previous work has demonstrated that cognitive motor dissociation (CMD) - brain activation detected by EEG in response to motor commands despite the absence of observable behavioral responses - is associated with long-term recovery. However, CMD testing has important limitations, including false-negative results in patients with aphasia, hearing impairment, language barriers, or fluctuating arousal.
Sleep architecture is profoundly disrupted after severe brain injury. Emerging evidence suggests that the presence of well-formed sleep spindles (WFSS) on EEG reflects preserved thalamocortical network integrity and is associated with recovery of consciousness and improved neurological outcomes. Sleep spindle detection offers a potentially scalable, inexpensive, and language-independent biomarker that can be obtained passively during routine EEG monitoring.
This study seeks to determine whether EEG sleep features, particularly WFSS, can improve prediction of early recovery of consciousness and long-term neurological outcomes while also developing novel EEG-based measures of functional network recovery.
Eligibility
Inclusion Criteria:
\- Adults with non-penetrating traumatic brain injury (TBI) or with primary intracerebral hemorrhage (ICH) (i.e. from hypertension or anticoagulants) who remain behaviorally unresponsive to verbal commands (i.e., comatose vegetative state, or minimally conscious state minus \[MCS-minus, defined as unresponsive with preserved visual fixation/pursuit or localization to noxious stimuli\]) by day 2 after injury
Exclusion Criteria:
- Evidence of consciousness within 2 days of injury
- Uncontrolled seizures
- pre-existing disorders of consciousness
- deafness
